
Runn is a real-time resource management platform with integrated time tracking and powerful forecasting capabilities.
Intuitively plan projects and schedule resources with allocations, project phases, milestones, and time off. Flick between monthly, quarterly and half-yearly views to plan for the short and long term. Get a dynamic bird’s-eye view of your entire organization to manage capacity, workload and availability changes as you create your plans.
Runn makes resource management dynamic and visual from a single, shared view. Drill into different roles, teams and tags to compare trends and understand which groups are overbooked. Plan out tentative projects to see how plans might change if work gets confirmed.
Track projects, view forecasts, and get relevant metrics within Runn. Get insights like utilization, project variance, and overall financial performance. Use Runn’s built-in timesheets to monitor project progress.
Runn integrates with Harvest, WorkflowMax, and Clockify. With the API, build your own integrations to connect Runn with your favorite tools.
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Most enterprises can report what AI cost them. Far fewer can say which team owns it, whether it was approved, or what it returned.
FinOpsly closes that gap. The platform governs AI spend on the same cost model that carries the cloud, data platform and SaaS an AI workload consumes, so a business unit sees the full cost of an AI initiative instead of four disconnected bills.
Capabilities include:
Cost estimation before deployment. Model an architecture and get a priced workload across model APIs, GPU capacity, warehouse consumption and storage, with the assumptions on screen. Weigh model choices against consumption you have actually measured.
Attribution that holds up in a chargeback cycle. Spend resolves to owners, teams, applications, business units and customers through hierarchies nine or more levels deep. Tagging is standardized across providers, keys and resources are labeled in bulk from plain-language rules, and whatever remains unattributed is published as a number, not absorbed.
Guardrails that act. Set budgets by project, team or API key. Catch anomalies with root cause and route them to whoever owns the resource. Surface waste that provider tooling misses, using FinOpsly's own detection models. Plan commitments across AWS, Azure and Google Cloud. Park idle compute on approved schedules, reversibly.
Financial results you can defend. Automated chargeback in a single cycle. Savings measured as what reached run-rate against a no-action baseline. Unit economics down to cost per call, per active user and per customer served.
For technology and finance leaders accountable for what AI spend returns.
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DoiT
DoiT is a global technology company that delivers a comprehensive cloud operations platform designed to optimize performance, scalability, and cost efficiency. Powered by proactive, industry-leading expertise, DoiT Cloud Intelligence is the only context-aware multicloud platform that turns insights into action.
With deep specializations in Kubernetes, GenAI, CloudOps, and FinOps, we partner with AWS, Google Cloud, and Microsoft Azure to help over 4,000 businesses worldwide enhance cloud performance, reliability, and security. Whether managing complex multicloud environments or driving innovation, DoiT provides the intelligence and human expertise needed to maximize your cloud investment.
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Corz Cloud
Corz Cloud Platform simplifies Hybrid Cloud Cost Management by providing an optimized solution for AWS Azure, Google Cloud, and Google Cloud. Corz Cloud Platform was designed for developers and managers. Now teams can directly access granular Cloud costs as well as Optimization recommendations. You can now set up automated policies to reduce Cloud expenses with a single click. You will receive notifications about cloud billing and usage anomalies. Cloud spending can be viewed across the enterprise by product owners. Get a detailed view of your Cloud spending. Get alerts when individual teams exceed their Cloud spending budgets. Set up a set of policies that can be applied across all teams. Identify resources that are not being used and create policies that can be run automatically. Identify the spending of each team across all Cloud Providers. Show back Cloud usage costs to individual teams. If resources are not being used, shut down them. Automated shutdown policies can help you reduce cloud spending.
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